Alcohol Abuse and Suicide Attempt in Iran: A Case-Crossover Study
Bibliographic record
Abstract
Alcohol use and its disorders are associated with increased risk of suicidal behaviors Research has shown that 6-8% of those who use alcohol have a history of suicide attempt. Given the prohibition of alcohol use legally, the increased alcohol consumption, and the lack of strong evidence in favor of its use associated with suicide in Iran, this study was conducted to determine the link between suicide attempt and alcohol abuse. The case-crossover method was used in this research. Out of 305 referrals to the emergency room due to a suicide attempt, 100 reported drinking alcohol up to six hours before their attempt. Paired Matching and Usual Frequency were employed to analyze the data with STATA 12.0. The probability of attempting suicide up to six hours after drinking alcohol appeared increased by 27 times (95% CI: 8.1-60.4). Separate analysis for each of these hours from the first to the sixth hour after alcohol use was also performed. Fifty percent of attempted suicides happened one hour after alcohol use. Relative risk for the first and second hour was 10% and 5% respectively. Alcohol use is a strong proximal risk factor for attempted suicide among Iranian subjects. Prevention of alcohol use should be considered in setting up of the national Suicide attempt prevention program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".